The automated visual inspection may function as an early recommendation system for manufacturing companies as
the increase in customer satisfaction in getting a defect free product is increasing day by day in the current market. These
removals of the defective products are now done manually, which is time consuming and costlier than the proposed model. The
key factor is to maximize the company’s profit in the coming years. In this paper a Residual Network (RESNET) Classifier and a
RESUNET Segmentation model.
The RESNET is a type of Convolutional Neural network (CNN) that can be used for prediction models. In this paper, there's an
investigation to predict the defective products from the non-defective products. The input is passed on the RESNET classifier and
RESUNET Segmentation model where the model predicts wheather the product is defective or not and gives us the result that
can be viewed by the user.